Antigoni Georgiadou

Bio

Antigoni Georgiadou is an Applied Mathematician at the Science Engagement Section, Algorithms & Performance Analysis (APA) Group. Dr. Georgiadou obtained her Ph.D. in Mathematics from Florida State University where she worked on optimization in stellar evolution applications. She received her bachelor’s degree in Applied Mathematics and Physical Sciences from the National Technical University of Athens, Greece in 2013. Dr. Georgiadou worked as a research assistant at the European Space Agency in Darmstadt, Germany, to apply machine learning (ML) methods for radiation belts profile predictions for the Integral and XMM-Newton satellites. In 2017, she joined as a URA visiting scholar, the Theoretical Astrophysics Group and the Machine Intelligence and Reconstruction Group at Fermilab in Batavia, Illinois, to work on an analysis to develop a statistical framework with Gaussian Processes and ML to optimize the input parameter space of cosmological simulations. Before joining the APA Group, Antigoni Georgiadou was a postdoctoral research associate in OLCF’s Advanced Computing for Nuclear, Particles, & Astrophysics Group.

Antigoni Georgiadou views theory as a way of enhancing understanding and as means of new algorithmic solutions. Astrophysics applications in the areas of cosmology and stellar evolution simulations have been motivating some of her research questions. As a member of the APA Group Dr. Georgiadou collaborates with application scientists from astrophysics and cosmology to optimize performance and requirements of applications on supercomputers. Antigoni Georgiadou is part of the ExaStar ECP project and partners with the ExaSky ECP project and the HACC team to enable science breakthroughs in cosmology.

Publications